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Overcoming Bias in Design _ UX Scotland

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Bias. We all deal with it, and we all have it. It’s baked into our brains, and into our social systems. It helps us make decisions - for better or (often) for worse. Every design and content decision we make has layers of assumptions hidden below the surface. And for those of us who are designers, builders and makers, those decisions can have real consequences for people’s lives. Our great challenge is to retain the assumptions that make us good at our jobs, while overcoming the ones that can harm or alienate the people we design for.

The way to deal with bias is not to ignore it, but to face it head-on, recognise it and work on it directly. In this session, I will cover the types of bias we experience in ourselves and others - particularly as designers and technology workers - with detailed examples of how that bias can result in harm.

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Overcoming Bias in Design _ UX Scotland

  1. 1. O V E R C O M I N G B I A S I N D E S I G N H E AT H E R O N E I L L P I X E L S F O R H U M A N S @pixelsforhumans
  2. 2. A P P L E H E A LT H F E AT U R E L I S T • Vitals • Exercise • Meals/Snacks • Sleep • Medication • Doctor visits/diagnoses • Etc… • Period Tracker
  3. 3. I N T E N T I S N O T M A G I C http://www.shakesville.com/2011/12/harmful- communication-part-one-intent.html
  4. 4. B I A S Noun. 
 1. An inclination towards one group over another group, often in an unfair way.
  5. 5. Do I contradict myself? Very well, then I contradict myself. I am large, I contain multitudes - Walt Whitman Me too, Walt.
  6. 6. meanawkward tall fast talking slow lazy unkind not smart lost liar dull
  7. 7. 0 3000000 6000000 9000000 12000000 Input Processed 11 millon 40
  8. 8. https://xkcd.com/610/
  9. 9. C O G N I T I V E B I A S
  10. 10. https://xkcd.com/1731/
  11. 11. - K AT E M E Y E R , N E L S O N N O R M A N G R O U P Flat interfaces often use weak signifiers…[which] require more user effort than strong ones. https://www.nngroup.com/articles/flat-ui-less-attention-cause-uncertainty/
  12. 12. S Y S T E M I C B I A S
  13. 13. # N O TA L L …
  14. 14. N U M B E R S D O N ’ T L I E
  15. 15. Algorithm = Data + Success Metric(s)
  16. 16. G A R B A G E I N G A R B A G E O U T
  17. 17. - C AT H Y O ’ N E I L , W E A P O N S O F M AT H D E S T R U C T I O N Algorithms don't make life more fair, they just automate the status quo. https://www.ted.com/talks/cathy_o_neil_the_era_of_blind_faith_in_big_data_must_end
  18. 18. “Sometimes unpleasant portrayals of sensitive subject matter online can affect what image search results appear for a given query. 
 
 These results don’t reflect Google’s own opinions or beliefs — as a company, we strongly value a diversity of perspectives, ideas and cultures.” http://www.huffingtonpost.co.uk/entry/three-black-teenagers- google-racism_uk_575811f5e4b014b4f2530bb5
  19. 19. D O N ’ T B E E V I L
  20. 20. D O N ’ T B E E V I L Stick our heads in the sand while we reinforce the historical evils of society.
  21. 21. D O N ’ T B E E V I L Stick our heads in the sand while we reinforce the historical evils of society.
  22. 22. You are less right than you think. You don’t know what you don’t know.
  23. 23. O V E R C O M I N G 
 B I A S
  24. 24. Social Cognitive E M PAT H Y Emotional feelings reactions reasonings mental models contexts structural biases
  25. 25. H O W C O U L D T H I S C A U S E H A R M ? A N D W H O D O E S T H I S H E L P ?
  26. 26. G O O G L E D U P L E X
  27. 27. J U S T L I S T E N
  28. 28. N O , S R S LY L I S T E N
  29. 29. I am…
  30. 30. L I S T Y O U R A S S U M P T I O N S
  31. 31. A U D I E N C E A S S U M P T I O N S • Mostly • white • able-bodied • cisgender • straight • male • UX designers • Care about people • If marginalized, will feel heard and not othered.
  32. 32. P R A C T I C E A P O L O G I Z I N G You’re going to get stuff wrong.
  33. 33. D O T H E W O R K .
  34. 34. http://newsletter.pixelsforhumans.com

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